{
"total": 359,
"categories": [
{
"category": "Attack",
"count": 74
},
{
"category": "Concept",
"count": 53
},
{
"category": "Protocol",
"count": 45
},
{
"category": "Tool",
"count": 41
},
{
"category": "Methodology",
"count": 40
},
{
"category": "Defense",
"count": 23
},
{
"category": "Certification",
"count": 19
},
{
"category": "Vulnerability",
"count": 17
},
{
"category": "Networking",
"count": 16
},
{
"category": "Role",
"count": 10
},
{
"category": "Slang",
"count": 6
},
{
"category": "Principles",
"count": 5
},
{
"category": "ICS",
"count": 4
},
{
"category": "AI/ML Security",
"count": 3
},
{
"category": "Hardware",
"count": 3
}
],
"skillLevels": [
{
"skill_level": "Intermediate",
"count": 183
},
{
"skill_level": "Advanced",
"count": 122
},
{
"skill_level": "Beginner",
"count": 54
}
]
}
curl --location --request GET 'https://zylalabs.com/api/14093/cyberdict+-+cybersecurity+glossary+api/34798/getstats' --header 'Authorization: Bearer YOUR_API_KEY'
{
"terms": [
{
"id": 362,
"term": "1337 (Leet)",
"short_description": "Alternative alphabet using symbols and numbers to replace letters, popular in hacker culture.",
"full_description": "1337 (pronounced \"leet\"), derived from \"elite\" is a type of internet slang where standard letters are replaced with various combinations of ASCII characters, numbers, and symbols. It originated in 1980s bulletin board systems and early hacker culture as a way to obfuscate text and demonstrate technical prowess. The simplest form replaces letters with similar-looking numbers (E=3, A=4, T=7, etc.), while more complex versions use creative substitutions. While less common in professional contexts today, elements of leet speak remain in technical culture, gaming communities, and as a way to bypass simple text filters.",
"category": "Slang",
"related_terms": "[\"Hacker Culture\",\"ASCII Art\",\"Obfuscation\",\"Internet Slang\",\"Text Substitution\"]",
"examples": "[\"Converting \\\"Hacker\\\" to \\\"H4ck3r\\\" or more extremely to \\\"|\\\\|4(|<3|2\\\"\",\"Using \\\"pwn\\\" (derived from \\\"own\\\" as \\\"p\\\" resembles \\\"o\\\" in some fonts) to indicate domination or compromise\",\"Creating passwords with leet substitutions (though predictable substitutions are vulnerable to rule-based cracking)\",\"Online handles and group names incorporating leet speak like \\\"Th3 R34l D34l\\\"\"]",
"skill_level": "Beginner"
},
{
"id": 361,
"term": "2FA (Two-Factor Authentication)",
"short_description": "Two-Factor Authentication - adds an extra verification layer beyond passwords",
"full_description": "Two-Factor Authentication (2FA) is a security method that requires users to provide two different authentication factors to verify themselves. This provides a higher level of security than single-factor authentication (like a password alone) because even if one factor is compromised, the second factor would still prevent unauthorized access. The factors typically come from different categories: something you know (password), something you have (security token or mobile device), or something you are (biometrics). Common implementations include sending a code via SMS, using an authenticator app to generate time-based one-time passwords (TOTP), or using hardware security keys.",
"category": "Defense",
"related_terms": "[\"MFA\",\"OTP\",\"TOTP\",\"Authentication\",\"Hardware Token\"]",
"examples": "[\"Using Google Authenticator to generate a verification code after entering a password\",\"Receiving a one-time code via SMS when logging into a banking website\",\"Plugging in a YubiKey hardware token to complete the login process\"]",
"skill_level": "Beginner"
},
{
"id": 360,
"term": "Actions on Objectives",
"short_description": "The final phase where attackers accomplish their goals in the target environment.",
"full_description": "Actions on Objectives is the final phase of the Cyber Kill Chain, where attackers accomplish their ultimate goals after establishing presence in the target environment. These objectives vary based on the attacker's motivations and might include data exfiltration, system or data destruction, ransomware deployment, espionage, or using the compromised system as a launching point for further attacks. This phase represents the culmination of the attack and often causes the most direct harm to the victim organization.",
"category": "Methodology",
"related_terms": "[\"Cyber Kill Chain\",\"Data Exfiltration\",\"Ransomware\",\"Espionage\",\"Destruction\"]",
"examples": "[\"Exfiltrating sensitive intellectual property to an attacker-controlled server\",\"Deploying ransomware across the network to encrypt critical business data\",\"Establishing persistence within critical infrastructure to enable future sabotage\"]",
"skill_level": "Intermediate"
},
{
"id": 359,
"term": "AdminSDHolder",
"short_description": "Active Directory protection mechanism that can be abused for persistence",
"full_description": "AdminSDHolder is a special object in Active Directory designed to protect privileged accounts from unauthorized modifications by enforcing a specific security descriptor. Every 60 minutes, a background process (SDProp) copies the AdminSDHolder's access control list to all protected accounts and groups. While this is a security feature, attackers can abuse it for persistence by modifying the AdminSDHolder object itself to grant themselves persistent access to all privileged accounts. Since these changes are continuously reapplied by the system, traditional remediation approaches may fail to remove the attacker's access.",
"category": "Vulnerability",
"related_terms": "[\"Active Directory\",\"Access Control List\",\"SDProp\",\"Protected Groups\",\"Persistence\",\"Security Descriptor\"]",
"examples": "[\"Adding a backdoor user to AdminSDHolder's ACL for persistent admin access\",\"Maintaining persistence that survives regular cleanup attempts\",\"Hiding access rights that propagate to all protected accounts\"]",
"skill_level": "Advanced"
},
{
"id": 358,
"term": "AdminSDHolder Abuse",
"short_description": "Exploiting the protected group mechanism in Active Directory to maintain persistent privileged access.",
"full_description": "AdminSDHolder abuse is a sophisticated persistence technique in Active Directory environments that exploits the AdminSDHolder object and Security Descriptor propagation mechanism. The AdminSDHolder object in Active Directory contains a security descriptor that is applied to protected groups (like Domain Admins) every 60 minutes by the SDProp process. By modifying the ACLs on the AdminSDHolder object, attackers can grant themselves persistent rights to all protected accounts and groups, even if direct permissions on those objects are later removed. This technique is particularly stealthy because it leverages a legitimate AD protection mechanism and the changes persist through regular security measures like password resets.",
"category": "Attack",
"related_terms": "[\"Active Directory\",\"Persistence\",\"ACL\",\"Protected Groups\",\"SDProp\"]",
"examples": "[\"Adding a 'Full Control' ACE for a backdoor account to the AdminSDHolder object\",\"Granting 'GenericAll' rights to maintain the ability to reset passwords of privileged accounts\",\"Using DCSync rights on AdminSDHolder to maintain the ability to extract password hashes\"]",
"skill_level": "Advanced"
},
{
"id": 357,
"term": "Admission Controller",
"short_description": "Kubernetes components intercepting requests to validate and mutate resources",
"full_description": "Admission Controllers in Kubernetes are plugins that intercept API requests to create, modify, or delete resources before they are persisted. These controllers serve two primary functions: validating requests against custom security policies, and mutating requests to enforce security controls or inject configuration. Security-focused admission controllers can enforce pod security standards, prevent privileged containers, implement network policies, and validate image sources. Tools like OPA Gatekeeper and Kyverno provide customizable policy enforcement through admission control.",
"category": "Defense",
"related_terms": "[\"Kubernetes\",\"Container Security\",\"Policy Enforcement\",\"Security Controls\",\"OPA\",\"Webhook\"]",
"examples": "[\"PodSecurityPolicy enforcing container security standards\",\"OPA Gatekeeper validating resource configurations against policies\",\"MutatingAdmissionWebhook injecting security sidecars automatically\"]",
"skill_level": "Advanced"
},
{
"id": 356,
"term": "Adversarial Example (AI/ML)",
"short_description": "Inputs to machine learning models intentionally designed to cause the model to make a mistake.",
"full_description": "An adversarial example in machine learning is an input that has been slightly modified in a way that is imperceptible to humans but causes a machine learning model (e.g., an image classifier, a spam filter) to misclassify it with high confidence. These attacks highlight vulnerabilities in ML models. Creating effective adversarial examples often requires knowledge of the model's architecture or access to query the model. Defending against them is an active area of research.",
"category": "AI/ML Security",
"related_terms": "[\"Machine Learning Security\",\"Data Poisoning\",\"Model Evasion\",\"AI Security\"]",
"examples": "[\"Adding a small, almost invisible noise pattern to an image of a panda, causing an image recognition model to classify it as a gibbon.\",\"Slightly altering a spam email to bypass a machine learning-based spam filter.\",\"Crafting audio commands that are unintelligible to humans but recognized by voice assistants.\"]",
"skill_level": "Advanced"
},
{
"id": 355,
"term": "AES (Advanced Encryption Standard)",
"short_description": "A symmetric block cipher widely adopted by the U.S. government and used worldwide."
}
],
"_note": "Response truncated for documentation purposes"
}
curl --location --request GET 'https://zylalabs.com/api/14093/cyberdict+-+cybersecurity+glossary+api/34799/listterms' --header 'Authorization: Bearer YOUR_API_KEY'
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|---|---|
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359个网络安全术语:攻击 CVE 工具 协议 概念 简短和完整的定义 示例 相关术语 技能等级 JSON
CyberDict 提供 359 个网络安全术语,包括名称、简短定义和完整定义、示例、相关术语、类别和技能水平。术语端点支持文本搜索、类别和技能水平过滤器、数字 ID 和分页。统计端点返回总数和计数。将其用于培训、测验、工具提示、聊天机器人和 SOC 入职。内容按原样提供用于教育和防御安全。未提供任何担保。对安全关键的信息进行核实,使用主要来源。不要将原始数据集作为竞争词汇表进行转售
使用listTerms端点 可选的q参数用于搜索术语 category和skill_level参数可以缩小结果 所有过滤器以AND组合 使用id来检索单个术语
使用限制控制返回的匹配项数量,使用偏移量跳过匹配项。两个参数都是可选的。术语按字母顺序排列
每个术语包含术语名称 简短定义 完整描述 示例 相关术语 类别和技能水平 技能水平分为初级 中级和高级 相关术语支持链接的词汇表和知识图谱
GetStats端点返回按类别和技能等级分类的总术语数量和计数 当前数据集包含359个术语 响应为JSON并由Cloudflare边缘提供